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Morphological analysis in epidemiological studies using growing and adaptive MEshes: Application to subcortical structures in AD

机译:流行病学研究中使用生长和适应性网格的形态学分析:在AD皮层下结构中的应用

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Detecting morphological changes in the brain is important for a better understanding of normal aging and brain disorders. Growing and Adaptive MEshes (GAMEs) is a multi-dimensional method for modeling complex brain structures and highlight significant differences between groups, such as healthy subjects versus patients with Alzheimer disease (AD). In this work, we have extended the functionalities of GAMEs by introducing a multidimensional analysis of linear correlation between local morphological changes and other independent variables, thus allowing for epidemiological studies. The new algorithm has been validated on a challenging medical application: the correlation of morphological changes in hippocampi and thalamus with the MMSE score, in a population of healthy subjects and patients with AD.
机译:检测大脑的形态变化对于更好地了解正常老化和脑疾病是重要的。生长和自适应网格(游戏)是一种用于建模复杂脑结构的多维方法,突出群体之间的显着差异,例如健康受试者与阿尔茨海默病(AD)的患者。在这项工作中,我们通过引入局部形态变化与其他独立变量与其他自变量之间的线性相关性的多维关系来扩展了游戏的功能。从而允许流行病学研究。新算法已在具有挑战性的医学应用中验证:海马和丘脑的形态变化与MMSE评分的相关性,在健康受试者和广告患者中。

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